What tools does Opsrift include?

Opsrift includes six product areas: (1) Postmortem Generator — 9-section incident postmortems; (2) Shift Handover Generator — structured handovers with auto-imported incidents; (3) Runbook Generator — operational runbooks from incidents or postmortems; (4) Incident Investigation — AI-assisted Q&A over your incident context; (5) Status Page — hosted public status with components and incidents; (6) Incident Forecast — proactive risk signals from your postmortem history. All six tools are available today.

How does Opsrift generate postmortems?

Opsrift uses Anthropic's Claude AI to generate 9 structured sections in parallel: Executive Summary, Timeline, Root Cause Analysis, Impact, Detection & Response, Resolution, Process & Organizational Gaps, Action Items, and Lessons Learned. Import from PagerDuty, OpsGenie, Datadog, Grafana, or Jira (where connected), or enter data manually.

What integrations are available?

Opsrift supports PagerDuty and OpsGenie for incident import, Datadog and Grafana for alert and metric import, Jira for import and action item push, Confluence for one-click publishing, Slack and Microsoft Teams for webhook notifications and summaries, and GitHub for deploy-to-incident correlation. All nine integrations are available now.

What does the Starter plan include?

The Starter plan at $10/month gives you 10 AI generations per month, all core tools (postmortem, handover, runbook, investigation), 1 status page, PagerDuty & OpsGenie import, and exports. Every plan includes a 7-day free trial — a card is required to start, but you can cancel anytime.

How to automate shift handovers?

Connect PagerDuty or Jira, define your shift window (including quick presets like last 8h / 12h / 24h), and Opsrift generates a 7-section handover with summary, active incidents, tasks, escalations, metrics, upcoming changes, and notes — in under a minute instead of a long verbal passdown.

What is Incident Forecast?

Incident Forecast analyzes your saved postmortem history to surface proactive risk signals: recurring systems, deploy-to-incident correlation, unresolved action item debt, severity trend (worsening/improving/stable), and mean time between incidents (MTBI). An AI-generated risk brief summarizes the overall picture so you can act before the next incident hits.

Can I edit the generated reports?

Yes. Every section can be edited inline or regenerated individually with AI. You can click any section heading to enter edit mode, make changes, and the report updates in real time. You can also regenerate a specific section while keeping the rest intact.

Is my incident data secure?

Yes. Opsrift uses Clerk for authentication, Supabase with Row Level Security for data storage, and all API calls are encrypted via HTTPS. Your incident data is only used to generate your reports and is never used for AI model training.

How to Automate Incident Postmortems

Every ops team knows they should write postmortems. Most don't do it consistently because the process is manual, time-consuming, and feels like paperwork after you've already spent hours fighting the fire. Automation doesn't replace the thinking — it eliminates the formatting, structuring, and data-gathering grunt work so your team can focus on analysis and action items.

If you're new to postmortems, start with What is an Incident Postmortem? for the fundamentals.

What Can Be Automated (and What Can't)

What automation handles well:

Pulling incident data from alerting tools (PagerDuty, OpsGenie, Datadog, Grafana)
Pulling ticket context from ITSM tools (Jira, ServiceNow)
Structuring the report into consistent sections
Generating timeline reconstructions from event data
Drafting impact summaries from metadata (duration, severity, affected services)
Formatting and exporting (PDF, Confluence, Markdown)

What still needs humans:

Root cause analysis (AI can suggest, but humans validate)
Action item prioritization based on business context
Lessons learned that connect to organizational patterns
Sign-off and review

The Manual Postmortem Workflow (And Where Time Gets Wasted)

Here's what the typical manual process looks like:

Incident resolves — engineer opens a blank doc or template
Copies incident details from PagerDuty or monitoring tool
Copies ticket info from Jira
Writes timeline from memory and chat logs
Drafts each section (summary, RCA, impact, actions)
Formats the document
Creates Jira tickets for action items manually
Publishes to Confluence or wiki manually
Links everything together

Steps 1–3 and 6–9 are pure overhead. The actual thinking happens in steps 4–5. That's maybe 30 minutes of a 2-hour process. The rest is copy-paste, formatting, and tool-switching.

The Automated Workflow

Step 1 — Connect Your Tools

Link PagerDuty and Jira once. Credentials are stored securely per-user and reused for every future postmortem. No re-authentication required.

Step 2 — Import the Incident

Select the incident from PagerDuty or Jira. All metadata — severity, timeline, affected services, responders — auto-fills into the generation form. No tab-switching or copy-pasting.

Step 3 — Generate

AI produces a complete structured postmortem using parallel section generation. Nine sections generated simultaneously in under 60 seconds. Each section uses a specialized prompt tuned for that part of the postmortem.

Step 4 — Review and Refine

Edit any section with an inline split editor (markdown on the left, live preview on the right). Regenerate individual sections if the AI missed context. This is where humans add judgment — validating root cause, adjusting action items, adding lessons from institutional knowledge.

Step 5 — Distribute

Push action items to Jira as tickets with automatic priority mapping. Publish the full report to Confluence with proper ADF formatting. Export as PDF, copy for Slack, or send to Microsoft Teams. The entire lifecycle — from incident data to published, actionable documentation — takes minutes instead of hours.

What to Look for in a Postmortem Automation Tool

Direct integration with your alerting tool (PagerDuty, OpsGenie, Datadog, Grafana) — not just copy-paste
Direct integration with your ITSM (Jira, ServiceNow) — both import AND push back
Consistent structure that meets your organization's postmortem template
Editable output — AI drafts, humans finalize
Export options that match where your team actually reads reports (Confluence, PDF, Slack, Microsoft Teams)
Security: your incident data shouldn't be used for model training

Opsrift was built specifically for this workflow — PagerDuty, OpsGenie, Datadog, Grafana, Jira, Slack, and Microsoft Teams integration, parallel AI generation, inline editing, and one-click Confluence publishing.

ROI of Postmortem Automation

Time saved: 1–2 hours per incident × number of incidents per month
Consistency: every postmortem follows the same structure regardless of who writes it
Completion rate: teams that automate write postmortems for more incidents because the barrier is lower
Action item follow-through: when items are pushed to Jira automatically, they're tracked instead of forgotten
Audit readiness: structured, timestamped documentation is always available

Frequently Asked Questions

Can AI write a postmortem by itself?

AI generates the structure and drafts content from incident data, but humans should review root cause analysis, validate action items, and add organizational context. Think of it as a first draft, not a final product.

What tools integrate with postmortem automation?

Look for tools that connect to PagerDuty, OpsGenie, Datadog, Grafana, Jira, Confluence, Slack, Microsoft Teams, and GitHub. Opsrift integrates natively with all nine: PagerDuty and OpsGenie (alert import), Datadog and Grafana (metric alert import), Jira (import + action item push), Confluence (one-click publish), Slack and Microsoft Teams (webhook notifications), and GitHub (deploy correlation).

Does automation make postmortems less thorough?

The opposite. Automation handles the tedious parts (formatting, data gathering, structuring) so the team has more time for the parts that matter: root cause analysis and action items.

How long does an automated postmortem take?

Generation takes under 60 seconds. Review and refinement depends on incident complexity — typically 15–30 minutes for a thorough review, compared to 1–3 hours fully manual.